A Network-Based Rating System and Its Resistance to Bribery
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence. Pages 301-306.
Abstract
We study a rating system in which a set of individuals (e.g., the customers of a restaurant) evaluate a given service (e.g, the restaurant), with their aggregated opinion determining the probability of all individuals to use the service and thus its generated revenue. We explicitly model the influence relation by a social network, with individuals being influenced by the evaluation of their trusted peers. On top of that we allow a malicious service provider (e.g., the restaurant owner) to bribe some individuals, i.e., to invest a part of his or her expected income to modify their opinion, therefore influencing his or her final gain. We analyse the effect of bribing strategies under various constraints, and we show under what conditions the system is bribery-proof, i.e., no bribing strategy yields a strictly positive expected gain to the service provider.
@inproceedings{ijcai2016p50,
title = {A Network-Based Rating System and Its Resistance to Bribery},
author = {Grandi, Umberto and Turrini, Paolo},
booktitle = {Proceedings of the Twenty-Fifth International Joint Conference on
Artificial Intelligence, {IJCAI-16}},
publisher = {AAAI Press / International Joint Conferences on Artificial Intelligence},
editor = {Subbarao Kambhampati},
pages = {301--306},
year = {2016},
month = {7},
url = {https://ijcai.org/proceedings/2016/50},
}
TY - CPAPER TI - A Network-Based Rating System and Its Resistance to Bribery AU - Grandi, Umberto AU - Turrini, Paolo T2 - Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, IJCAI-16 PB - AAAI Press / International Joint Conferences on Artificial Intelligence PY - 2016 SP - 301 EP - 306 UR - https://ijcai.org/proceedings/2016/50 ER -Copied
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